High body mass index is associated with elevated risk of perioperative ischemic stroke in patients who underwent noncardiac surgery: A retrospective cohort study

Abstract Background Body mass index (BMI) serves as a global metric for assessing obesity and overall health status. However, the impact of BMI, treated as a continuous variable, on the risk of perioperative stroke remains poorly understood. This retrospective cohort study aimed to elucidate the association between BMI and the risk of perioperative ischemic stroke in patients undergoing non‐cardiovascular surgery. Methods A cohort of 223,415 patients undergoing noncardiac surgery at the First Medical Center of Chinese PLA General Hospital between January 1, 2008 and August 31, 2019 was screened. Preoperative high BMI, defined as BMI >22.64 kg/m2, was the primary exposure, and the outcome of interest was the new diagnosis of perioperative ischemic stroke within 30 days post‐surgery. Robust controls for patient and intraoperative factors were implemented to minimize residual confounding. Logistic regression and propensity score matching were employed, and patients were stratified into subgroups for further investigation. Results The overall incidence of perioperative ischemic stroke was 0.23% (n = 525) in the cohort. After adjusting for patient‐related variables (OR 1.283; 95% CI, 1.04–1.594; p < 0.05), surgery‐related variables (OR 1.484; 95% CI, 1.2–1.849; p < 0.001), and all confounding variables (OR 1.279; 95% CI, 1.025–1.607; p < 0.05), patients with BMI >22.64 kg/m2 exhibited a significantly increased risk of perioperative ischemic stroke. This association persisted in the propensity score matched cohort (OR 1.577; 95% CI, 1.203–2.073; p < 0.01). Subgroup analyses indicated that preoperative BMI >22.64 kg/m2 correlated with an elevated risk of perioperative ischemic stroke in female patients, those with coronary heart disease, peripheral vascular diseases, and individuals undergoing neurosurgery. Conclusion We first identified BMI >22.64 kg/m2 as a substantial and independent risk factor for perioperative ischemic stroke in Chinese noncardiac surgery patients. Normal BMI may not suffice as a universal preventive standard. Instead, a more stringent perioperative weight management approach is recommended, particularly for specific subgroups such as female patients, those with coronary heart disease and peripheral vascular disease, and individuals scheduled for neurosurgery.


| INTRODUC TI ON
Stroke stands as the world's second leading cause of death, contributing to 10%-15% of global mortality. 1Perioperative stroke, defined as ischemic or hemorrhagic cerebral infarction during or within 30 days after surgery, though occurring at a relatively low incidence (0.1-1.0%), [2][3][4] carries a staggering fatality rate of approximately 50% within a decade. 5Hindered by delayed diagnostic imaging, a narrow intervention window, and heightened bleeding risks, <5% of eligible patients benefit from thrombolysis, resulting in a majority facing a bleak prognosis. 6Recognizing the urgency of this issue, active preoperative intervention in risk factors emerges as pivotal for averting perioperative stroke occurrences.
Body mass index (BMI), derived by dividing weight (kg) by the square of height (m), serves as an international standard gauging obesity and overall health.Elevated BMI often leads to metabolic disorders, predisposing individuals to various diseases.2][13] However, the relationship between BMI and perioperative stroke remains contentious.
Previous investigations have yielded conflicting findings; a retrospective study identified a BMI of ≥25 kg/m 2 as an independent risk factor for perioperative stroke in patients undergoing percutaneous coronary intervention. 14Conversely, two large-scale studies proposed that a higher BMI (35.0-40.0kg/m 2 ) may confer protective effects against perioperative stroke. 3,15Meanwhile, several clinical studies found no significant association between BMI and perioperative stroke risk. 8,16Notably, these studies treated BMI as a categorical variable, despite its inherent nature as a continuous measure reflecting the nuanced relationship between weight and height.
To address this gap, we present the first systematic study exploring the association between BMI as a continuous variable and the risk of perioperative ischemic stroke.This retrospective study encompasses 223,415 Chinese noncardiac surgery patients and aims to shed light on the nuanced relationship between BMI and perioperative stroke risk.Given the ethnic variations in BMI classifications and the absence of research on this topic within the Chinese surgical population, our study provides valuable insights to the global understanding of perioperative stroke risks.

| Ethical approval and compliance
The study was conducted in accordance with the approved research protocol by the Medical Ethics Committee of the Chinese PLA General Hospital (reference number: S2021-493-01).The requirement for written informed consent was waived.The manuscript adheres to the applicable Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines (Table S1).S2).A flowchart illustrating the patient screening process is presented in Figure 1.

| Outcome and exposure measures
The primary outcome of interest was perioperative ischemic stroke, defined as neurological dysfunction (motor, sensory, or cognitive) attributable to focal cerebral, spinal, or retinal infarction within 30 perioperative days. 17Diagnosis was confirmed through discharge records containing at least one ICD-9-CM/ICD-10-CM code for stroke (Table S2).The exposure of interest was preoperative body mass index (BMI), which was stratified into BMI Normal BMI may not suffice as a universal preventive standard.Instead, a more stringent perioperative weight management approach is recommended, particularly for specific subgroups such as female patients, those with coronary heart disease and peripheral vascular disease, and individuals scheduled for neurosurgery.

K E Y W O R D S
BMI, continuous variable, non-cardiovascular surgery, optimal cutoff value, perioperative ischemic stroke ≤22.64 kg/m 2 and BMI >22.64 kg/m 2 based on receiver operating characteristic curve analysis.

| Covariates and data collection
We considered 34 potential confounders, categorized as patientrelated and surgery-related.Patient-related confounders included: age, sex, ASA classification, hypertension, diabetes mellitus, stroke, history of chronic cerebrovascular disease, coronary heart disease, arterial fibrillation, valvular heart disease, myocardial infarction, history of cardiac surgery, peripheral vascular disease, renal dysfunction, preoperative use of β-blockers, aspirin, and statin; as well as indices derived from the preoperative laboratory data preoperative, such as hemoglobin, albumin, total bilirubin, prothrombin time, neutrophil-to-lymphocyte ratio (NLR), and platelet-to-lymphocyte ratio (PLR).These were collected from most recent blood counts measured within 3 days prior to surgery.Surgery-related confounders encompassed surgical type, duration, time of perioperative mean arterial pressure (MAP) >60 min, estimated blood loss, blood products depot, morphine equivalents, inhalation anesthetics, hormones, nonsteroidal anti-inflammatory drugs (NSAIDs), colloids infusion, and crystalloids infusion.

| Statistical analysis
Logistic regression analysis was employed to assess the relationship between BMI and the risk of perioperative ischemic stroke.and standardized mean difference (SMD) were applied to assess the balance of covariates between the two groups, with an SMD <0.2 deemed as acceptable deviations for each covariate. 18,19The association between perioperative ischemic stroke and BMI was estimated using logistic regression analysis.
Sex, coronary heart disease, peripheral vascular disease, and type of surgery were associated with the risk of high BMI complications in several previous studies. 7,20Consequently, we conducted subgroup analyses based on these factors, using unadjusted variables with Bonferroni correction for multiple comparisons.1 and Figure 2).

| Primary analysis
Of the entire cohort, 525 patients experienced perioperative ischemic stroke within 30 days of surgery.Unadjusted logistic regression analysis revealed a significant association between BMI >22.64 kg/m 2 and the risk of perioperative ischemic stroke (OR  2).Table S3 details the complete data used in these models.

| PSM analysis and adjustment
PSM analysis, as described in the methods section, resulted in matched cohorts of 59,746 patients in the BMI ≤22.64 kg/m 2 group and 59,746 patients in the BMI >22.64 kg/m 2 group, with K-densities similar between the two groups (Figure 2A,B).Logistic regression analysis confirmed a significant association between BMI >22.64 kg/ m 2 and the risk of perioperative ischemic stroke (OR 1.577; 95% CI, 1.203-2.073;p < 0.01; Table 2).Detailed data are provided in Table S4.

| Subgroup analysis
Subgroup analyses based on sex, coronary heart disease, peripheral vascular disease, and surgery type were conducted (Figure 3).In the

Note:
The data are shown as the median (interquartile range), n (%), or mean ± SD.

| DISCUSS ION
Perioperative stroke represents a significant and independent complication of surgery, associated with heightened risks of physical disability, cognitive dysfunction, and mortality. 213][24][25][26] While a BMI >30 kg/m 2 has been established as a risk factor for stroke in general, 27 the association between BMI and perioperative stroke remains controversial.Our study contributes to this discourse by systematically investigating the relationship between BMI as a continuous variable and the risk of perioperative ischemic In our analysis of 223,415 patients undergoing noncardiac surgery, the overall incidence of perioperative ischemic stroke was 0.23%, aligning with international studies 28 and a prior investigation. 29We innovatively explored BMI as a continuous variable to establish a clear cutoff for perioperative ischemic stroke risk.Strikingly, unadjusted data analysis demonstrated a significant association between BMI >22.64 kg/m 2 and an increased risk of perioperative The propensity score histograms of the two groups.(A) Before matching.(B) After matching.We observed a stronger association between BMI >22.64 kg/m 2 and perioperative ischemic stroke in females, patients with coronary heart disease, those with peripheral vascular disease, and in cases involving neurosurgery.Again, this aligns with previous literature that has reported similar associations within these subgroups in separate cohorts.A previous study showed that female is associated with more than a threefold increased risk of perioperative stroke, 31 which may be related to the slower metabolism of female patients with increased BMI having, which is more likely to cause abnormal blood lipid metabolism, resulting in the weakening of the automatic regulation of cerebral blood flow.Other studies showed that the effect of sexual dimorphism about age on the matching between local neuronal activity and regional cerebral blood flow only apparent in females but not males, it may be related to the loss of estrogen in postmenopausal women, which could lead to a greater decline in cerebral blood flow. 32,33Similarly, others have found that patients with high BMI and diabetes have increased postoperative complications, 34 and that the risk of stroke was higher with vascular and neurosurgical operations. 28Interestingly, the association of BMI > 22.64 kg/m 2 with perioperative ischemic stroke was also evident in the neurosurgical subgroup, calling for increased attention to patients in this subgroup that must undergo neurosurgery.This subgroup analysis underscores the importance of considering patient characteristics when evaluating the impact of BMI on perioperative stroke risk.
The strengths of our study include the extensive patient sample size, the innovative exploration of BMI as a continuous variable, and the identification of a clear cutoff value for perioperative stroke risk.The integration of comprehensive preoperative, intraoperative, and perioperative data enhances the robustness of our findings.Additionally, sensitivity analyses, including PSM and subgroup F I G U R E 3 Subgroup analysis of the association between BMI and the risk of perioperative ischemic stroke.OR, odds ratio; BMI, body mass index.
analyses, consistently validated the robustness of the observed association.
Despite these strengths, our study has limitations.BMI, while commonly used, lacks precision in distinguishing lean from fat mass and providing insights into fat distribution.The single-hospital data source may limit generalizability.Despite adjusting for numerous confounders, residual and unmeasured confounders may persist in observational studies.The risk factors causing gender differences in perioperative stroke with high BMI have not been identified.And future investigations should explore the association between high BMI and long-term survival outcomes following perioperative ischemic stroke.

| CON CLUS ION
In summary, our study unequivocally establishes a significant association between BMI >22.64 kg/m 2 and an elevated risk of perioperative ischemic stroke.BMI >22.64 kg/m 2 emerged as an independent risk factor for perioperative ischemic stroke in our comprehensive analysis.Contrary to the conventional notion of maintaining a normal BMI as a universal standard for preventing perioperative ischemic stroke, our findings highlight the need for nuanced considerations, particularly in specific patient populations.
Our results underscore the importance of tailored perioperative weight management strategies, particularly for female patients, those with coronary heart disease and peripheral vascular disease, and individuals undergoing neurosurgery.Our study first identified BMI >22.64 kg/m 2 as an independent risk factor that prompts a call for heightened vigilance and targeted interventions in these highrisk subgroups to mitigate the risk of perioperative ischemic stroke.
As we navigate the complexities of perioperative care, these findings contribute valuable insights to the refinement of clinical practices.Future research should explore the applicability of our results across diverse populations and delve into the long-term implications of perioperative ischemic stroke in individuals with elevated BMI.Ultimately, our study advocates for a personalized approach to perioperative weight management to optimize patient outcomes and enhance the overall quality of surgical procedure.
This retrospective cohort study included patients who underwent noncardiac surgery at the First Medical Center of Chinese PLA General Hospital, a tertiary referral academic hospital in Beijing, China, between January 1, 2008 and August 31, 2019.Patients meeting the following criteria were included: (1) undergoing noncardiac surgery, (2) age ≥ 18 years, (3) duration of surgery >60 min, (4) general anesthesia, (5) American Society of Anesthesiologists (ASA) physical status <V, and (6) complete data for all confounders.For individuals with multiple surgeries during the study period, only data from the first qualifying surgery were included.Patients diagnosed with perioperative ischemic stroke were identified through ICD-9/10 diagnosis codes (Table

Four
models were constructed: Model 1 (unadjusted), Model 2 (adjusted for patient-related confounders), Model 3 (adjusted for surgery-related confounders), and Model 4 (fully adjusted to patientrelated and surgery-related confounders).To enhance comparability, 1:1 propensity score matching (PSM) was performed using a logistic regression model and the following covariates: age, sex, ASA class, surgery type, duration of procedures, hypertension, diabetes mellitus, coronary heart disease, peripheral vascular disease, preoperative Hb, preoperative β-blockers, NSAIDs, colloids infusion, and crystalloids infusion.Matched or weighted data, Kernel density plots Statistical significance was set at p < 0.05.R program (version 1.4.1106,R Foundation for Statistical Computing, Vienna, Austria) and relevant packages (tableone, MatchIt, pROC, Matching, Cobalt, rms, and car) were utilized for statistical analyses.

3 | RE SULTS 3 . 1 |
Baseline patient characteristicsThe study included 223,415 patients undergoing noncardiac surgery at the Chinese PLA General Hospital between January 1, 2008 and August 31, 2019.Patients were stratified into two groups based on BMI: F I G U R E 1 Study flow diagram.ASA, American Society of Anesthesiologists; BMI, body mass index; PSM, propensity score matching.TA B L E 1 Baseline characteristics unadjusted sample and propensity score-matched sample.

TA B L E 2 5 million
Logistic regression and propensity score analysis of the association between high BMI and perioperative ischemic stroke.ischemic stroke.The subsequent adjustment for patient-related and surgery-related confounders, along with an extensive set of 34 prospectively defined confounders, consistently confirmed this association.Utilizing propensity score matching (PSM), we obtained balanced cohorts and reaffirmed a significant link between high BMI and the risk of perioperative ischemic stroke.Our findings are notably congruent with a study involving 0.Chinese individuals, where a BMI >23 kg/m 2 was associated with an increased risk of stroke.30This underscores the consistency of our results and highlights the potential clinical relevance of identifying a clear BMI threshold, such as 22.64 kg/m 2 , for preventing perioperative stroke in the Chinese surgical population.More importantly, we first identified BMI >22.64 kg/m 2 as a substantial and independent risk factor for perioperative ischemic stroke in Chinese noncardiac surgery patients.However, existing literature on the association between BMI and perioperative stroke has presented conflicting evidence.For example, others have identified BMI ≥25 kg/m 2 significantly increased the risk of perioperative stroke in patients undergoing percutaneous coronary intervention,14 but an American study including 350,031 noncardiac, non-neurologic patients, found BMI 35-40 kg/m 2 appeared to have a protective effect against perioperative stroke. 3Varied results may be attributed to differences in surgical populations, racial disparities, and the categorical treatment of BMI, potentially overlooking the nuanced impact of normal BMI as a risk factor for perioperative stroke.Future studies with larger sample sizes and diverse populations are warranted to elucidate these relationships further.Subgroup analyses based on sex, coronary heart disease, peripheral vascular disease, and surgery type provided additional insights.
119,491 pairs were matched by propensity score.Full results are displayed in TableS4.
Abbreviation: CI, confidence interval; OR, odds ratio; PS, propensity score.aModel 1 was a univariable crude model.bModel 2 included age, sex, ASA Class, hypertension, diabetes mellitus, stroke, history of chronic cerebrovascular disease, coronary heart disease, arterial fibrillation, valvular heart disease, myocardial infarction, history of cardiac surgery, peripheral vascular disease, renal dysfunction, and preoperative use of β-blockers, aspirin and statin, preoperative ALB, preoperative TBIL, preoperative PT, preoperative NLR, and preoperative PLR.c Model 3 included surgical type, duration of surgery, time of perioperative MAP >60 min, estimated blood loss, blood products depot, morphine equivalents, inhalation anesthetics, hormones, and NSAIDs, colloids infusion, and crystalloids infusion.dModel4 includes all the above confounders.Full results are displayed in TableS3.e